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We consider the problem of maximizing the spread of influence in a social network by choosing a fixed number of initial seeds, formally referred to as the influence maximization problem. It admits a $(1-1/e)$-factor approximation algorithm…

Social and Information Networks · Computer Science 2022-06-15 Grant Schoenebeck , Biaoshuai Tao

Students' decisions on whether to take a class are strongly affected by whether their friends plan to take the class with them. A student may prefer to be assigned to a course they likes less, just to be with their friends, rather than…

Artificial Intelligence · Computer Science 2023-09-19 Ilya Khakhiashvili , Lihi Dery , Tal Grinshpoun

Members of social networks are given opportunities to bestow positive recognition upon one another by means of constructs such as "likes" and "retweets." Although recipients no doubt experience utility from these actions, one might question…

Social and Information Networks · Computer Science 2016-06-17 Stan Palasek

The advent of online social networks has facilitated fast and wide spread of information. However, some users, especially members of minority groups, may be less likely to receive information spreading on the network, due to their…

Social and Information Networks · Computer Science 2025-12-18 Changan Liu , Xiaotian Zhou , Ahad N. Zehmakan , Zhongzhi Zhang

We consider influence maximization (IM) in social networks, which is the problem of maximizing the number of users that become aware of a product by selecting a set of "seed" users to expose the product to. While prior work assumes a known…

Machine Learning · Computer Science 2018-05-25 Sharan Vaswani , Branislav Kveton , Zheng Wen , Mohammad Ghavamzadeh , Laks Lakshmanan , Mark Schmidt

We consider the problem of selecting a seed set to maximize the expected number of influenced nodes in the social network, referred to as the \textit{influence maximization} (IM) problem. We assume that the topology of the social network is…

Machine Learning · Computer Science 2019-11-26 Xiaojin Zhang

Influence maximization is the problem of finding the set of nodes of a network that maximizes the size of the outbreak of a spreading process occurring on the network. Solutions to this problem are important for strategic decisions in…

Physics and Society · Physics 2019-10-23 Sirag Erkol , Claudio Castellano , Filippo Radicchi

Given a large population, it is an intensive task to gather individual preferences over a set of alternatives and arrive at an aggregate or collective preference of the population. We show that social network underlying the population can…

Social and Information Networks · Computer Science 2017-11-17 Swapnil Dhamal , Rohith D. Vallam , Y. Narahari

We study the adaptive influence maximization problem with myopic feedback under the independent cascade model: one sequentially selects k nodes as seeds one by one from a social network, and each selected seed returns the immediate…

Social and Information Networks · Computer Science 2019-05-29 Binghui Peng , Wei Chen

We study the optimal pricing strategy of a monopolist selling homogeneous goods to customers over multiple periods. The customers choose their time of purchase to maximize their payoff that depends on their valuation of the product, the…

Computer Science and Game Theory · Computer Science 2018-06-28 Ali Makhdoumi , Azarakhsh Malekian , Asuman Ozdaglar

An informed planner wishes to spread information among a group of agents in order to induce efficient coordination -- say the adoption of a new technology with positive externalities. The agents are connected via a social network. The…

Theoretical Economics · Economics 2024-02-09 Yu Awaya , Vijay Krishna

In social networks, individuals' decisions are strongly influenced by recommendations from their friends and acquaintances. The influence maximization (IM) problem asks to select a seed set of users that maximizes the influence spread,…

Social and Information Networks · Computer Science 2020-08-21 Alessio Arleo , Walter Didimo , Giuseppe Liotta , Silvia Miksch , Fabrizio Montecchiani

The influence maximization (IM) problem aims at finding a subset of seed nodes in a social network that maximize the spread of influence. In this study, we focus on a sub-class of IM problems, where whether the nodes are willing to be the…

Social and Information Networks · Computer Science 2021-06-15 Haipeng Chen , Wei Qiu , Han-Ching Ou , Bo An , Milind Tambe

Given a social network $G$, the profit maximization (PM) problem asks for a set of seed nodes to maximize the profit, i.e., revenue of influence spread less the cost of seed selection. The target profit maximization (TPM) problem, which…

Social and Information Networks · Computer Science 2019-10-30 Keke Huang , Jing Tang , Xiaokui Xiao , Aixin Sun , Andrew Lim

Influence maximization serves as the main goal of a variety of social network activities such as viral marketing and campaign advertising. The independent cascade model for the influence spread assumes a one-time chance for each activated…

Social and Information Networks · Computer Science 2017-08-08 Ali Vardasbi , Heshaam Faili , Masoud Asadpour

Influence propagation has been the subject of extensive study due to its important role in social networks, epidemiology, and many other areas. Understanding propagation mechanisms is critical to control the spread of fake news or…

Optimization and Control · Mathematics 2022-09-28 Vinicius Ferreira , Artur Pessoa , Thibaut Vidal

We consider the *adaptive influence maximization problem*: given a network and a budget $k$, iteratively select $k$ seeds in the network to maximize the expected number of adopters. In the *full-adoption feedback model*, after selecting…

Social and Information Networks · Computer Science 2022-06-15 Wei Chen , Binghui Peng , Grant Schoenebeck , Biaoshuai Tao

A simple advertising strategy that can be used to help increase sales of a product is to mail out special offers to selected potential customers. Because there is a cost associated with sending each offer, the optimal mailing strategy…

Artificial Intelligence · Computer Science 2013-01-18 David Maxwell Chickering , David Heckerman

Influence diffusion and influence maximization in large-scale online social networks (OSNs) have been extensively studied, because of their impacts on enabling effective online viral marketing. Existing studies focus on social networks with…

Social and Information Networks · Computer Science 2012-12-04 Yanhua Li , Wei Chen , Yajun Wang , Zhi-Li Zhang

We consider stochastic influence maximization problems arising in social networks. In contrast to existing studies that involve greedy approximation algorithms with a 63% performance guarantee, our work focuses on solving the problem…

Social and Information Networks · Computer Science 2020-06-02 Hao-Hsiang Wu , Simge Kucukyavuz